Phylogenomic analyses and reclassification of the Mesorhizobium complex: proposal for 9 novel genera and reclassification of 15 species.

BACKGROUD: The genus Mesorhizobium is shown by phylogenomics to be paraphyletic and forms part of a complex that includes the genera Aminobacter, Aquamicrobium, Pseudaminobacter and Tianweitania. The relationships for type strains belong to these genera need to be carefully re-evaluated. RESULTS: The relationships of Mesorhizobium complex are evaluated based on phylogenomic analyses and overall genome relatedness indices (OGRIs) of 61 type strains. According to the maximum likelihood phylogenetic tree based on concatenated sequences of 539 core proteins and the tree constructed using the bac120 bacterial marker set from Genome Taxonomy Database, 65 type strains were grouped into 9 clusters. Moreover, 10 subclusters were identified based on the OGRIs including average nucleotide identity (ANI), average amino acid identity (AAI) and core-proteome average amino acid identity (cAAI), with AAI and cAAI showing a clear intra- and inter-(sub)cluster gaps of 77.40-80.91% and 83.98-86.16%, respectively. Combined with the phylogenetic trees and OGRIs, the type strains were reclassified into 15 genera. This list includes five defined genera Mesorhizobium, Aquamicrobium, Pseudaminobacter, Aminobacterand Tianweitania, among which 40/41 Mesorhizobium species and one Aminobacter species are canonical legume microsymbionts. The other nine (sub)clusters are classified as novel genera. Cluster III, comprising symbiotic M. alhagi and M. camelthorni, is classified as Allomesorhizobium gen. nov. Cluster VI harbored a single symbiotic species M. albiziae and is classified as Neomesorhizobium gen. nov. The remaining seven non-symbiotic members were proposed as: Neoaquamicrobium gen. nov., Manganibacter gen. nov., Ollibium gen. nov., Terribium gen. nov., Kumtagia gen. nov., Borborobacter gen. nov., Aerobium gen. nov.. Furthermore, the genus Corticibacterium is restored and two species in Subcluster IX-1 are reclassified as the member of this genus. CONCLUSION: The Mesorhizobium complex are classified into 15 genera based on phylogenomic analyses and OGRIs of 65 type strains. This study resolved previously non-monophyletic genera in the Mesorhizobium complex.

Refining the taxonomy of the order Hyphomicrobiales (Rhizobiales) based on whole genome comparisons of over 130 type strains.

The alphaproteobacterial order Hyphomicrobiales consists of 38 families comprising at least 152 validly published genera as of January 2024. The order Hyphomicrobiales was first described in 1957 and underwent important revisions in 2020. However, we show that several inconsistencies in the taxonomy of this order remain and we argue that there is a need for a consistent framework for defining families within the order. We propose a common genome-based framework for defining families within the order Hyphomicrobiales, suggesting that families represent monophyletic groups in core-genome phylogenies that share pairwise average amino acid identity values above ~75 % when calculated from a core set of 59 proteins. Applying this framework, we propose the formation of four new families and to reassign the genera Salaquimonas, Rhodoblastus, and Rhodoligotrophos into Salaquimonadaceae fam. nov., Rhodoblastaceae fam. nov., and Rhodoligotrophaceae fam. nov., respectively, and the genera Albibacter, Chenggangzhangella, Hansschlegelia, and Methylopila into Methylopilaceae fam. nov. We further propose to unify the families Bartonellaceae, Brucellaceae, Phyllobacteriaceae, and Notoacmeibacteraceae as Bartonellaceae; the families Segnochrobactraceae and Pseudoxanthobacteraceae as Segnochrobactraceae; the families Lichenihabitantaceae and Lichenibacteriaceae as Lichenihabitantaceae; and the families Breoghaniaceae and Stappiaceae as Stappiaceae. Lastly, we propose to reassign several genera to existing families. Specifically, we propose to reassign the genus Pseudohoeflea to the family Rhizobiaceae; the genera Oricola, Roseitalea, and Oceaniradius to the family Ahrensiaceae; the genus Limoniibacter to the emended family Bartonellaceae; the genus Faunimonas to the family Afifellaceae; and the genus Pseudochelatococcus to the family Chelatococcaceae. Our data also support the recent proposal to reassign the genus Prosthecomicrobium to the family Kaistiaceae.

Rhizobium nodule diversity and composition are influenced by clover host selection and local growth conditions.

While shaping of plant microbiome composition through 'host filtering' is well documented in legume-rhizobium symbioses, it is less clear to what extent different varieties and genotypes of the same plant species differentially influence symbiont community diversity and composition. Here, we compared how clover host varieties and genotypes affect the structure of Rhizobium populations in root nodules under conventional field and controlled greenhouse conditions. We first grew four Trifolium repens (white clover) F2 crosses and one variety in a conventional field trial and compared differences in root nodule Rhizobium leguminosarum symbiovar trifolii (Rlt) genotype diversity using high-throughput amplicon sequencing of chromosomal housekeeping (rpoB and recA) genes and auxiliary plasmid-borne symbiosis genes (nodA and nodD). We found that Rlt nodule diversities significantly differed between clover crosses, potentially due to host filtering. However, variance in Rlt diversity largely overlapped between crosses and was also explained by the spatial distribution of plants in the field, indicative of the role of local environmental conditions for nodule diversity. To test the effect of host filtering, we conducted a controlled greenhouse trial with a diverse Rlt inoculum and several host genotypes. We found that different clover varieties and genotypes of the same variety selected for significantly different Rlt nodule communities and that the strength of host filtering (deviation from the initial Rhizobium inoculant composition) was positively correlated with the efficiency of symbiosis (rate of plant greenness colouration). Together, our results suggest that selection by host genotype and local growth conditions jointly influence white clover Rlt nodule diversity and community composition.

International Committee on Systematics of Prokaryotes, Subcommittee on the taxonomy of Rhizobia and Agrobacteria, minutes of the annual meeting by videoconference, 5 July 2021, followed by online discussion until 31 December 2021.

Minutes of the closed meeting of the International Committee on Systematics of Prokaryotes Subcommittee on the Taxonomy of Rhizobia and Agrobacteria held by videoconference, 5 July 2021, followed by online discussion until 31 December 2021, and list of recent species.

Genetic variation is associated with differences in facilitative and competitive interactions in the Rhizobium leguminosarum species complex.

Competitive and facilitative interactions influence bacterial community composition, diversity and functioning. However, the role of genetic diversity for determining interactions between coexisting strains of the same, or closely related, species remains poorly understood. Here, we investigated the type (facilitative/inhibitory) and potential underlying mechanisms of pairwise interactions between 24 genetically diverse bacterial strains belonging to three genospecies (gsA,C,E) of the Rhizobium leguminosarum species complex. Interactions were determined indirectly, based on secreted compounds in cell-free supernatants, and directly, as growth inhibition in cocultures. We found supernatants mediated both facilitative and inhibitory interactions that varied greatly between strains and genospecies. Overall, gsE strains indirectly suppressed growth of gsA strains, while their own growth was facilitated by other genospecies' supernatants. Similar genospecies-level patterns were observed in direct competition, where gsA showed the highest susceptibility and gsE the highest inhibition capacity. At the genetic level, increased gsA susceptibility was associated with a non-random distribution of quorum sensing and secondary metabolite genes across genospecies. Together, our results suggest that genetic variation is associated with facilitative and competitive interactions, which could be important ecological mechanisms explaining R. leguminosarum diversity.

User-friendly bioinformatics pipeline gDAT (graphical downstream analysis tool) for analysing rDNA sequences.

High-throughput sequencing (HTS) of multiple organisms in parallel (metabarcoding) has become a routine and cost-effective method for the analysis of microbial communities in environmental samples. However, careful data treatment is required to identify potential errors in HTS data, and the large volume of data generated by HTS requires in-house experience with command line tools for downstream analysis. This paper introduces a pipeline that incorporates the most common command line tools into an easy-to-use graphical interface-gDAT. By using the Python scripting language, the pipeline is compatible with the latest Windows, macOS and Linux operating systems. The pipeline supports analysis of Sanger, 454, IonTorrent, Illumina and PacBio sequences, allows custom modification of quality filtering steps, and implements both open and closed-reference operational taxonomic unit-picking for sequence identification. Predefined parameters are optimized for analysis of small subunit (SSU) rRNA gene amplicons from arbuscular mycorrhizal fungi, but the pipeline is widely applicable to metabarcoding studies targeting a broad range of organisms. The pipeline was additionally tested with data using general eukaryotic primers from the SSU gene region and fungal primers from the internal transcribed spacer (ITS) marker region. We describe the pipeline design and evaluate its performance and speed by conducting analysis of example data sets using different marker regions sequenced on Illumina platforms. The graphical interface, with the option to use the command line if needed, provides an accessible tool for rapid data analysis with repeatability and logging capabilities. Keeping the software open-source maximizes code accessibility, allowing scrutiny and bug fixes by the community.

Defining the Rhizobium leguminosarum Species Complex.

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at approximately 96% ANI, implying that it is a 'natural' unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, "R. indicum" and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterize isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterizing the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains.

MAUI-seq: Metabarcoding using amplicons with unique molecular identifiers to improve error correction.

Sequencing and PCR errors are a major challenge when characterizing genetic diversity using high-throughput amplicon sequencing (HTAS). We have developed a multiplexed HTAS method, MAUI-seq, which uses unique molecular identifiers (UMIs) to improve error correction by exploiting variation among sequences associated with a single UMI. Erroneous sequences are recognized because, across the data set, they are over-represented among the minor sequences associated with UMIs. We show that two main advantages of this approach are efficient elimination of chimeric and other erroneous reads, outperforming dada2 and unoise3, and the ability to confidently recognize genuine alleles that are present at low abundance or resemble chimeras. The method provides sensitive and flexible profiling of diversity and is readily adaptable to most HTAS applications, including microbial 16S rRNA profiling and metabarcoding of environmental DNA.

International Committee on Systematics of Prokaryotes Subcommittee on the Taxonomy of Rhizobia and Agrobacteria Minutes of the closed meeting by videoconference, 17 July 2019.

Minutes of the closed meeting of the ICSP Subcommittee on the Taxonomy of Rhizobia and Agrobacteria held by videoconference on 17 July 2019, and list of recent species.

International Committee on Systematics of Prokaryotes Subcommittee on the Taxonomy of Rhizobia and Agrobacteria Minutes of the meeting by video conference, 11 July 2018.

Minutes of the meeting of the Subcommittee on the Taxonomy of Rhizobia and Agrobacteria (ICSP), video conference on 11 July 2018.

Defining functional diversity for lignocellulose degradation in a microbial community using multi-omics studies.

BACKGROUND: Lignocellulose is one of the most abundant forms of fixed carbon in the biosphere. Current industrial approaches to the degradation of lignocellulose employ enzyme mixtures, usually from a single fungal species, which are only effective in hydrolyzing polysaccharides following biomass pre-treatments. While the enzymatic mechanisms of lignocellulose degradation have been characterized in detail in individual microbial species, the microbial communities that efficiently breakdown plant materials in nature are species rich and secrete a myriad of enzymes to perform "community-level" metabolism of lignocellulose. Single-species approaches are, therefore, likely to miss important aspects of lignocellulose degradation that will be central to optimizing commercial processes. RESULTS: Here, we investigated the microbial degradation of wheat straw in liquid cultures that had been inoculated with wheat straw compost. Samples taken at selected time points were subjected to multi-omics analysis with the aim of identifying new microbial mechanisms for lignocellulose degradation that could be applied in industrial pre-treatment of feedstocks. Phylogenetic composition of the community, based on sequenced bacterial and eukaryotic ribosomal genes, showed a gradual decrease in complexity and diversity over time due to microbial enrichment. Taxonomic affiliation of bacterial species showed dominance of Bacteroidetes and Proteobacteria and high relative abundance of genera Asticcacaulis, Leadbetterella and Truepera. The eukaryotic members of the community were enriched in peritrich ciliates from genus Telotrochidium that thrived in the liquid cultures compared to fungal species that were present in low abundance. A targeted metasecretome approach combined with metatranscriptomics analysis, identified 1127 proteins and showed the presence of numerous carbohydrate-active enzymes extracted from the biomass-bound fractions and from the culture supernatant. This revealed a wide array of hydrolytic cellulases, hemicellulases and carbohydrate-binding modules involved in lignocellulose degradation. The expression of these activities correlated to the changes in the biomass composition observed by FTIR and ssNMR measurements. CONCLUSIONS: A combination of mass spectrometry-based proteomics coupled with metatranscriptomics has enabled the identification of a large number of lignocellulose degrading enzymes that can now be further explored for the development of improved enzyme cocktails for the treatment of plant-based feedstocks. In addition to the expected carbohydrate-active enzymes, our studies reveal a large number of unknown proteins, some of which may play a crucial role in community-based lignocellulose degradation.

Horizontal Transfer of Symbiosis Genes within and Between Rhizobial Genera: Occurrence and Importance.

Rhizobial symbiosis genes are often carried on symbiotic islands or plasmids that can be transferred (horizontal transfer) between different bacterial species. Symbiosis genes involved in horizontal transfer have different phylogenies with respect to the core genome of their ‘host’. Here, the literature on legume⁻rhizobium symbioses in field soils was reviewed, and cases of phylogenetic incongruence between rhizobium core and symbiosis genes were collated. The occurrence and importance of horizontal transfer of rhizobial symbiosis genes within and between bacterial genera were assessed. Horizontal transfer of symbiosis genes between rhizobial strains is of common occurrence, is widespread geographically, is not restricted to specific rhizobial genera, and occurs within and between rhizobial genera. The transfer of symbiosis genes to bacteria adapted to local soil conditions can allow these bacteria to become rhizobial symbionts of previously incompatible legumes growing in these soils. This, in turn, will have consequences for the growth, life history, and biogeography of the legume species involved, which provides a critical ecological link connecting the horizontal transfer of symbiosis genes between rhizobial bacteria in the soil to the above-ground floral biodiversity and vegetation community structure.

Coordinated regulation of core and accessory genes in the multipartite genome of Sinorhizobium fredii.

Prokaryotes benefit from having accessory genes, but it is unclear how accessory genes can be linked with the core regulatory network when developing adaptations to new niches. Here we determined hierarchical core/accessory subsets in the multipartite pangenome (composed of genes from the chromosome, chromid and plasmids) of the soybean microsymbiont Sinorhizobium fredii by comparing twelve Sinorhizobium genomes. Transcriptomes of two S. fredii strains at mid-log and stationary growth phases and in symbiotic conditions were obtained. The average level of gene expression, variation of expression between different conditions, and gene connectivity within the co-expression network were positively correlated with the gene conservation level from strain-specific accessory genes to genus core. Condition-dependent transcriptomes exhibited adaptive transcriptional changes in pangenome subsets shared by the two strains, while strain-dependent transcriptomes were enriched with accessory genes on the chromid. Proportionally more chromid genes than plasmid genes were co-expressed with chromosomal genes, while plasmid genes had a higher within-replicon connectivity in expression than chromid ones. However, key nitrogen fixation genes on the symbiosis plasmid were characterized by high connectivity in both within- and between-replicon analyses. Among those genes with host-specific upregulation patterns, chromosomal znu and mdt operons, encoding a conserved high-affinity zinc transporter and an accessory multi-drug efflux system, respectively, were experimentally demonstrated to be involved in host-specific symbiotic adaptation. These findings highlight the importance of integrative regulation of hierarchical core/accessory components in the multipartite genome of bacteria during niche adaptation and in shaping the prokaryotic pangenome in the long run.

Revealing the insoluble metasecretome of lignocellulose-degrading microbial communities.

Microbial communities metabolize plant biomass using secreted enzymes; however, identifying extracellular proteins tightly bound to insoluble lignocellulose in these microbiomes presents a challenge, as the rigorous extraction required to elute these proteins also lyses the microbes associated with the plant biomass releasing intracellular proteins that contaminate the metasecretome. Here we describe a technique for targeting the extracellular proteome, which was used to compare the metasecretome and meta-surface-proteome of two lignocellulose-degrading communities grown on wheat straw and rice straw. A combination of mass spectrometry-based proteomics coupled with metatranscriptomics enabled the identification of a unique secretome pool from these lignocellulose-degrading communities. This method enabled us to efficiently discriminate the extracellular proteins from the intracellular proteins by improving detection of actively secreted and transmembrane proteins. In addition to the expected carbohydrate active enzymes, our new method reveals a large number of unknown proteins, supporting the notion that there are major gaps in our understanding of how microbial communities degrade lignocellulosic substrates.